The Aw-Rascle-Zhang (ARZ) model can be interpreted as a gener-alization of the rst order Lighthill-Whitham-Richards (LWR) model, possessinga family of fundamental diagram curves, rather than a single one. We investi-gate to which extent this generalization increases the predictive accuracy of themodels. To that end, a systematic comparison of two types of data-tted LWRmodels and their second order ARZ counterparts is conducted, via a version ofthe three-detector problem test. The parameter functions of the models are con-structed using historic fundamental diagram data. The model comparisons arethen carried out using time-dependent data, of two very dierent types: vehicletrajectory data, and single-loop sensor data. The study of these PDE models iscarried out in a macroscopic sense, i.e., continuous eld quantities are constructedfrom the discrete data, and discretization eects are kept negligibly small.
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